About

Anurag Goyal is a skilled Data Science professional with 2 years of experience in solving business problems using data and machine learning. He is currently working as a Senior Unit Manager, Data Science at Bajaj Finance Limited. Anurag has a Bachelor of Technology degree in Civil Engineering from the Indian Institute of Technology, Delhi. Anurag is proficient in Python, SQL, Pyspark, MATLAB, and web scraping. He has worked on different use cases like propensity model for various financial products, customer segmentation, and delivered multiple data-driven campaigns for various business verticals using NLP, Clustering, Deep learning, and other ML techniques. Anurag has developed Random Forest-based propensity models across multiple businesses (FD, MF) using SMS and clickstream. He has also extracted mobile numbers of users with negative play store reviews and implemented LSTM model for classification of reviews to identify and rectify different pain points followed by an outcalling process improving app rating significantly. Anurag has employed RegEx on transactional SMS data to create 120+ independent variables and performed customer segmentation on 2cr+ customers using K means clustering resulting in 7 different clusters. In his past role as a Unit Manager, Data Science at Bajaj Finance Limited, Anurag performed web scraping on one of the major eCommerce websites using Beautiful Soup and selenium to categorize online purchases by customers which further helped in customer segmentation and recommendation engine on their marketplace. He also leveraged app-based alternate data to gather intelligence from off-us transactions and delivered multiple data-driven campaigns for UPI, PPI, BBPS verticals resulting in 10x monthly BBPS transactions on BFL super app within 6 months. Anurag also developed bank account statement-level reports for 2 lakh Personal Loan applicants per month using NLP on alternate data reducing the need for submission of physical statements and expediting customer journey. Prior to Bajaj Finance Limited, Anurag worked as a Data Analyst at ifsttar where he statistically analyzed passenger mobility survey data of 10 European nations with an aim to strengthen EU mobility system. He proposed better alternatives for redundant transit routes and transport services and presented an exhaustive report including graphical comparisons, solutions to Sogeti group of Capgemini at Luxembourg. Anurag has a strong technical background and is skilled in Data Scientist, Research Scientist, Random Forest, ML, SQL, NLP, Deep Learning, Web, Python, Mobile, Selenium, Neural Networks, Jupyter